agents.anac.y2011.HardHeaded

Class KLH

java.lang.Object

negotiator.Agent

agents.anac.y2011.HardHeaded.KLH

public class KLH
extends Agent

This class contains main agent methods and algorithms that agent uses in a negotiation session based on Alternating Offers protocol.

Author:

Siamak Hajizadeh, Thijs van Krimpen, Daphne Looije

Field Summary

Fields inherited from class negotiator.Agent

fNegotiation, parametervalues, sessionNr, sessionsTotal, startTime, strategyParameters, timeline, totalTime, utilitySpace

Constructor Summary

Constructors

Constructor and Description
KLH()

Method Summary

Methods

Modifier and Type	Method and Description
Action	chooseAction() This is the main strategy of that determines the behavior of the agent.
double	get_p() This function calculates the concession amount based on remaining time, initial parameters, and, the discount factor.
java.lang.String	getName()
static java.lang.String	getVersion()
void	init() handles some initializations.
void	ReceiveMessage(Action pAction) Receives opponent's action

Methods inherited from class negotiator.Agent

endSession, getAgentID, getParameterValues, getSessionNumber, getSessionsTotal, getStrategyParameters, getUtility, internalInit, isUIAgent, loadSessionData, parseStrategyParameters, restartDataObjectsFolder, saveSessionData, setAgentID, setName, sleep

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

KLH

public KLH()

Method Detail

init

public void init()

handles some initializations. it is called when agent object is created to start a negotiation session

Overrides:

init in class Agent

getVersion

public static java.lang.String getVersion()

getName

public java.lang.String getName()

Overrides:

getName in class Agent

Returns:

name of the agent.

ReceiveMessage

public void ReceiveMessage(Action pAction)

Receives opponent's action

Overrides:

ReceiveMessage in class Agent

get_p

public double get_p()

This function calculates the concession amount based on remaining time, initial parameters, and, the discount factor.

Returns:

double: concession step

chooseAction

public Action chooseAction()

This is the main strategy of that determines the behavior of the agent. It uses a concession function that in accord with remaining time decides which bids should be offered. Also using the learned opponent utility, it tries to offer more acceptable bids.

Specified by:

chooseAction in class Agent

Returns:

Action that contains agents decision